Covid 19 Analysis using Python

Importing modules

Task 1

Task 1.1:

Loading the Dataset

Task 1.2:

let's check the dataframe

let's check the shape of the dataframe

Task 2.1 :

let's do some preprocessing

let's see Global spread of Covid19

Task 2.2 : Exercise

Let's see Global deaths of Covid19

Task 3.1:

Let's Visualize how intensive the Covid19 Transmission has been in each of the country

let's start with an example:

let's select the columns that we need

calculating the first derivation of confrimed column

Task 3.2:

Let's Calculate Maximum infection rate for all of the countries

Task 3.3:

let's create a new Dataframe

Let's plot the barchart : maximum infection rate of each country

log to increase the quALITY FOR low bars - changes scale for y axis

Task 4: Let's See how National Lockdowns Impacts Covid19 transmission in Italy

COVID19 pandemic lockdown in Italy

On 9 March 2020, the government of Italy under Prime Minister Giuseppe Conte imposed a national quarantine, restricting the movement of the population except for necessity, work, and health circumstances, in response to the growing pandemic of COVID-19 in the country. source

let's get data related to italy

lets check the dataframe

let's calculate the infection rate in Italy

ok! now let's do the visualization

Task 5: Let's See how National Lockdowns Impacts Covid19 active cases in Italy

let's calculate number of active cases day by day

let's check the dataframe again

now let's plot a line chart to compare COVID19 national lockdowns impacts on spread of the virus and number of active cases

COVID19 pandemic lockdown in Germany

Lockdown was started in Freiburg, Baden-Württemberg and Bavaria on 20 March 2020. Three days later, it was expanded to the whole of Germany

let's select the data related to Germany

let's check the dataframe

selecting the needed column

let's check it again

let's calculate the infection rate in Germany

let's check the dataframe

now let's plot the line chart

- Saif Sayeed, Syed